'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
The Multicanonical Monte Carlo (MMC) technique
is a new form of adaptive importance sampling (IS). Thanks to
its blind adaptation algorithm, it does not require an in-depth
system knowledge for exploitation as does traditional IS. Hence
MMC is a practical, handy tool to estimate via simulation the
probability of rare events in complex telecom systems, such as
the symbol error rate or the outage probability. In this paper,
we present the analytical connections between MMC and IS, and
describe the recursive algorithm via which MMC seeks an optimal
“flat-histogram” warping. We also provide practical guidelines
on how MMC can be successfully applied in telecom to achieve
accelerations of simulation time by many orders of magnitude with
respect to standard Monte Carlo
